Senior Data Engineer, AI Platform & MLOps

Servco Pacific Inc; Honolulu (HI); On-site; USD 94,000 - 143,000; Full time

Job summary

Servco Pacific Inc. in Honolulu is seeking a Data Engineer III, AI Platform, to design, build, and operate reusable data pipelines and AI-ready platform services for Hawaii Mobility.

You will work on Databricks and Azure, delivering production-grade pipelines, data quality controls, and governance. The role requires 6–10 years of experience in data engineering, strong Python, SQL, Spark, and Databricks, and a track record with MLOps/LLMOps patterns.

Qualifications

• 6–10 years building production data pipelines and platforms with Python, SQL, Spark, and Databricks on Azure or a comparable cloud.
• Experience building reusable frameworks, automated tests, CI/CD, infrastructure as code, and observable production services.
• Hands-on AI-ready pipelines for features, retrieval corpora, or evaluation data, with MLOps/LLMOps deployment and monitoring experience.

Responsibilities

• Build and own reusable ingestion, transformation, orchestration, and serving patterns across batch and streaming workloads on Databricks.
• Implement automated data quality, lineage, and access controls for reliable AI contexts.
• Engineer feature, context, and retrieval pipelines with embeddings, metadata, and indexes.
• Develop AI-enabled services and MLOps/LLMOps components in collaboration with Data AI Architect.
• Mentor engineers through reviews and pairing; contribute to scalable patterns and runbooks.

Skills

Python

SQL

Spark

Databricks

Azure

MLOps

LLMOps

CI/CD

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Azure

Unity Catalog

MLflow

Vector search

OpenAI

Job description

Servco Pacific Inc. in Honolulu is seeking a Data Engineer III, AI Platform, to design, build, and operate reusable data pipelines and AI-ready platform services for Hawaii Mobility.

You will work on Databricks and Azure, delivering production-grade pipelines, data quality controls, and governance. The role requires 6–10 years of experience in data engineering, strong Python, SQL, Spark, and Databricks, and a track record with MLOps/LLMOps patterns.